The rapid growth in computer, the Internet, and telecommunication technology has brought about a change in how product manufacturers sell their goods. While brick and mortar establishments still provide an outlet for goods, running an ecommerce website is relatively inexpensive compared to a brick and mortar establishment and this has led to a large number of online retailers. In order to remain competitive, it can be important for online retailers to monitor competitor's prices and offerings. Manufacturers also have an interest in monitoring the pricing and availability of their products that are sold through online retailers.
There are times when a person, a vendor, or a manufacturer wants to create a list of products being sold at a list of retailers. In this scenario, the goal is to identify closely related products being sold at different merchants. These closely related products can be either identical, or similar in nature. The information regarding the closely related products is useful for various applications, including competitive pricing, enforcing minimum price monitoring (MAP) violation, commerce analytics, and marketing.
Unfortunately, the process of identifying closely related products is typically a manual and cumbersome task. The task is often dependent on the subjective judgment of a user conducting the task. Different persons may disagree on criterion of how to define a set of closely related products. Whether multiple products are similar to each other can be confirmed or denied based on different criteria. Furthermore, the user conducting the task may not fully understand the criteria to make an appropriate judgment on the criteria.